Dr. Calhoun develops techniques for making sense of complex brain imaging data. Because each imaging modality has limitations, the integration of these data is needed to understand the healthy and especially the disordered human brain.

Dr. Calhoun has created algorithms that map dynamic networks of brain function, structure and genetics, and how these are affected while being stimulated by various tasks or in individuals with mental illness such as schizophrenia.

For more information on Dr. Calhoun, please refer to his Curriculum Vitae or visit the Medical Image Analysis Lab. His CV includes his academic career, as well as grant history, professional service, a partial list of publications and a full bibliography.

Dr. Calhoun recently received fellowship designations for both the American Association for the Advancement of Science (AAAS) and the Institute of Electrical and Electronics Engineers (IEEE).

The organizations recognize Dr. Calhoun for his contributions to human brain research. One of Calhoun’s most significant accomplishments is his development of advanced algorithms that identify how brain regions ‘talk’ to one another either during a specific task or when at rest.

He also recently earned the A. Earl Walker Neuroscience Research Award, which recognizes outstanding contributions to basic or clinical research in neuroscience by a member of the faculty in any UNM department.

Each brain imaging modality reports on a different aspect of the brain with different strengths and weaknesses and there are now literally thousands of putative imaging biomarkers. This project will develop multivariate methods which use higher order statistics to combine diverse information in a scalable manner, identify correspondence among data types and also provide a sophisticated data sharing and management system.

Exploring similarity and differences among schizophrenia and bipolar disorder by combining fMRI and

This project will develop an exploratory data fusion model which combines 2 multivariate methods and is able to identify correspondence among multiple data types. We aim to apply this model to schizophrenia and bipolar disorder via an fMRI-DTI fusion, which can identify both shared and disease-specific brain abnormalities from multiple perspectives (brain function and structure).

"An author [or researcher] should never conceive
himself as bringing into existence beauty or
wisdom which did not exist before, but simply
and solely as trying to embody in terms of his
own art some reflection of eternal Beauty and
Wisdom...And always, of every idea and of every
method the Christian will ask not, 'Is it mine?'
but 'Is it good?'" - CS Lewis